import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation
from tensorflow.keras.optimizers import SGD

import numpy as np

x_train = np.random.random([1000, 20])
y_train = keras.utils.to_categorical(
    np.random.randint(10, size=(1000, 1)),
    num_classes=10
)

x_test = np.random.random((100, 20))
y_test = keras.utils.to_categorical(
    np.random.randint(10, size=(100, 1)),
    num_classes=10
)

model = Sequential()

model.add(Dense(64, activation='relu', input_dim=20))
model.add(Dropout(0.5))
model.add(Dense(64, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(10, activation='softmax'))

sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)

model.compile(
    loss='categorical_crossentropy',
    optimizer=sgd,
    metrics=['accuracy']
)

model.fit(x_train, y_train, epochs=20, batch_size=128)

score = model.evaluate(x_test, y_test, batch_size=128, verbose=2)

tf.print(score)
